
doi: 10.2307/2533167
Summary: \textit{J. Öfversten} [ibid. 49, No. 1, 45-57 (1993; Zbl 0771.62053)] presented two kinds of exact \(F\)-tests for variance components in unbalanced mixed linear models. Specifically, methods were developed for models with one random factor, nested classifications, and models with interaction between random factors. We discuss generalizations and conceptual simplifications of these methods.
Analysis of variance and covariance (ANOVA), exact \(F\)-tests, random effects, unbalanced mixed models, linear models, Parametric hypothesis testing
Analysis of variance and covariance (ANOVA), exact \(F\)-tests, random effects, unbalanced mixed models, linear models, Parametric hypothesis testing
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
